mirror of
https://github.com/chrisnov-it/quantumbotx.git
synced 2026-07-28 03:07:53 +00:00
53ae5e8861
- Update `app.py` to include backtesting routes and improve blueprint registration. - Modify templates to include an active page parameter for navigation highlighting. - Remove unused `crypto_data.py` and `api_crypto.py`. - Add new backtesting-related files and templates.
123 lines
5.5 KiB
Python
123 lines
5.5 KiB
Python
# core/backtesting/engine.py
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from core.strategies.strategy_map import STRATEGY_MAP
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def run_backtest(strategy_id, params, historical_data_df):
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"""
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Menjalankan simulasi backtesting untuk strategi tertentu pada data historis.
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"""
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strategy_class = STRATEGY_MAP.get(strategy_id)
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if not strategy_class:
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return {"error": "Strategi tidak ditemukan"}
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# Inisialisasi state backtesting
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trades = []
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in_position = False
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initial_capital = 10000 # Modal awal virtual $10,000
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capital = initial_capital
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equity_curve = [initial_capital]
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peak_equity = initial_capital
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max_drawdown = 0.0
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position_type = None
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entry_price = 0.0
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sl_pips = params.get('sl_pips', 100)
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tp_pips = params.get('tp_pips', 200)
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# Asumsi pip value sederhana untuk backtesting, bisa disempurnakan nanti
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# Untuk pair JPY, point adalah 0.001, untuk yang lain 0.00001
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point = 0.001 if 'JPY' in historical_data_df.columns[0].upper() else 0.00001
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# Asumsi nilai per pip untuk 0.01 lot
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# Ini adalah penyederhanaan besar, tapi cukup untuk backtesting awal
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value_per_pip = 0.1 # $0.10 per pip
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pip_value = 10 * point
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# Mock bot object untuk strategi
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class MockBot:
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def __init__(self):
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self.market_for_mt5 = "BACKTEST"
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self.timeframe = "H1"
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self.tf_map = {}
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# Inisialisasi strategi dengan parameter yang diberikan
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strategy_instance = strategy_class(bot_instance=MockBot(), params=params)
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# Loop melalui setiap bar data historis
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for i in range(1, len(historical_data_df)):
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# Buat DataFrame "seolah-olah" ini adalah data real-time hingga bar saat ini
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# PERBAIKAN: Gunakan .copy() untuk membuat salinan eksplisit dari slice.
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# Ini akan menghilangkan SettingWithCopyWarning di semua strategi.
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current_market_data = historical_data_df.iloc[:i].copy()
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analysis = strategy_instance.analyze(current_market_data)
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signal = analysis.get("signal")
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current_price = historical_data_df.iloc[i]['close']
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# Cek SL/TP jika sedang dalam posisi
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if in_position:
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profit = 0
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if position_type == 'BUY':
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profit_pips = (current_price - entry_price) / point / 10
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if current_price <= entry_price - (sl_pips * pip_value):
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trades.append({'entry': entry_price, 'exit': current_price, 'profit_pips': profit_pips, 'reason': 'SL'})
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capital += profit_pips * value_per_pip
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in_position = False
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elif current_price >= entry_price + (tp_pips * pip_value):
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trades.append({'entry': entry_price, 'exit': current_price, 'profit_pips': profit_pips, 'reason': 'TP'})
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capital += profit_pips * value_per_pip
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in_position = False
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elif position_type == 'SELL':
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profit_pips = (entry_price - current_price) / point / 10
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if current_price >= entry_price + (sl_pips * pip_value):
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trades.append({'entry': entry_price, 'exit': current_price, 'profit_pips': profit_pips, 'reason': 'SL'})
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capital += profit_pips * value_per_pip
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in_position = False
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elif current_price <= entry_price - (tp_pips * pip_value):
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trades.append({'entry': entry_price, 'exit': current_price, 'profit_pips': profit_pips, 'reason': 'TP'})
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capital += profit_pips * value_per_pip
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in_position = False
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if not in_position: # Jika posisi baru saja ditutup
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equity_curve.append(capital)
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peak_equity = max(peak_equity, capital)
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drawdown = (peak_equity - capital) / peak_equity
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max_drawdown = max(max_drawdown, drawdown)
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# Cek sinyal baru
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if signal == 'BUY' and not in_position:
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in_position = True
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position_type = 'BUY'
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entry_price = current_price
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elif signal == 'SELL' and not in_position:
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in_position = True
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position_type = 'SELL'
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entry_price = current_price
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elif (signal == 'SELL' and in_position and position_type == 'BUY') or \
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(signal == 'BUY' and in_position and position_type == 'SELL'):
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# Sinyal berlawanan, tutup posisi lama
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profit_pips = ((current_price - entry_price) if position_type == 'BUY' else (entry_price - current_price)) / point / 10
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trades.append({'entry': entry_price, 'exit': current_price, 'profit_pips': profit_pips, 'reason': 'Signal Flip'})
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capital += profit_pips * value_per_pip
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equity_curve.append(capital)
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peak_equity = max(peak_equity, capital)
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drawdown = (peak_equity - capital) / peak_equity
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max_drawdown = max(max_drawdown, drawdown)
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in_position = False
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# Hitung hasil akhir
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total_profit_pips = sum(trade['profit_pips'] for trade in trades)
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wins = len([trade for trade in trades if trade['profit_pips'] > 0])
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losses = len(trades) - wins
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win_rate = (wins / len(trades) * 100) if trades else 0
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return {
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"total_trades": len(trades),
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"total_profit_pips": total_profit_pips,
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"win_rate_percent": win_rate,
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"wins": wins,
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"losses": losses,
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"max_drawdown_percent": max_drawdown * 100,
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"equity_curve": equity_curve,
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"trades": trades[-20:] # Tampilkan 20 trade terakhir
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} |